Finding the "Right" Price

New tools promise to help the buy side look beyond the sticker price to reveal the total cost of purchase. With better tools we may one day get to the place where every price is truly the right price.

[From iSource Business, August 2001] Last month's Net Best column examined sell-side software that allows suppliers to optimize their selling processes, including finding the right price and managing customer response processes more strategically. This month, we look at the buy side of the equation and examine tools that help companies look beyond the sticker price to calculate the total cost of a purchase.

What is the Right Price?

For suppliers, it's that level that maintains the supplier's margins while also meeting strategic business goals. For buyers, the price issue encompasses more than just the figure that winds up on the sales contract. Total cost of purchase (TCP) clearly includes factors that have traditionally been calculated in total cost of ownership, such as quality, supplier reliability, lead times and warranty. However, TCP also encompasses more abstract factors, such as the risks of buying too much or too little of a component; the tradeoffs of buying one product over another, similar good; and the costs associated with doing business with a particular supplier under a given set of terms as opposed to slightly different terms.

The emergence of e-procurement has arguably made figuring the total cost of any given purchase considerably more difficult, because e-procurement systems have the potential to expose purchasers to a greater number of potential suppliers and therefore an exponentially broader range of options. Using manual processes to calculate total cost of purchase has never been easy because of the fuzziness of TCP's constituent components. But manual processes are a greater liability today because they impede the ability of a company and its supply chain to react to changes in demand or unexpected bottlenecks. Companies striving to operate in proverbial Internet time need TCP-discovery tools that enable them to rapidly respond in a dynamic way to fluctuations in the market.

No single solution provider, to date, has stepped forward with an application that can address every aspect of TCP. But several software and consulting companies have recently touted solutions that address some component of the total-cost-of-purchase equation.

The Cost of Too Few and Too Many

Sun Microsystems, for example, is using software from Rapt to examine the costs associated with buying too much or too little of key components for the company's servers. The ordinary challenges associated with planning supply to meet future demand are exacerbated in the computer industry by demand lead times that are shorter than supply lead times for key components.

Because the supply planning decisions must be made far in advance of actual customer orders, explains Ben Ma, director of supply planning at Sun, these decisions will always involve risk. We need to understand those risks, especially the impact that long-lead-time components have on our ability to meet demand and protect profits.

Sun had been using a manual process to calculate the level of buffer stocks it needed to keep on hand for key components shared across product lines. But this process could not take into account financial risks, such as the bottom-line impact, should the company run out of some components (lost sales, expediting costs) or overstock others (inventory costs, stock write-offs).

This dilemma is not unique to Sun, according to Pierre Mitchell, an analyst with technology consulting firm AMR Research. In direct procurement and the supply chain, the sourcing of purchased goods is quite often a binary decision between setting up a long-term contract with a key supplier or going to the spot market, Mitchell writes in an analysis that looked at Rapt. There is usually no system-supported method of risk management that determines whether the option to lock in contracted supply outweighs inventory exposure and possible favorable pricing fluctuations. The imprecise, deterministic and reductionist algorithms employed by reorder point, MRP [manufacturing resource planning] and even APS [advanced planning and scheduling] techniques do not adequately express the complexity of dynamic sourcing decisions that need to be made in the supply chain.

Rapt, with a background in building analytic applications to apply decision science to manufacturing, focuses particularly on this dilemma. It unveiled its Rapt Buy software in August 2000 and announced Sun as a client shortly thereafter, which is not surprising considering that Rapt CEO Tom Chavez cofounded his company after working on the short predictable lead-time initiative at Sun.

Rapt Buy synthesizes product and component data, sales data and targets for revenue and margins to give a company's planning group insight into total cost exposure for direct goods. Rapt Buy lets people take that uncertainty into account and helps to reveal the risk, says Dan Reidy, director of corporate marketing for Rapt. The software maps the costs of buying certain quantities of a product, given changes in market conditions. For example, Reidy explains, a graph shows the point at which this component will run out and you won't be able to make any more of this product. If you need more of this component on short notice, it'll cost you twice as much to fulfill that demand.

Sun reports that by using Rapt Buy it has reduced its exposure to excess supply costs by between 14 percent and 18 percent, and it has also reduced the costs of maintaining buffer stocks by 11 percent. Such results come at a price, of course: Rapt licenses its Buy application and also charges fees for the implementation, with an installation running from $500,000 up to several million dollars, depending on the size of the customer and how many products or components the company is trying to bring into the system at once.

The Price of Tradeoffs

Other solution providers are attacking TCP by moving the supplier-selection process online and automating certain steps in that process. For example, online negotiation and strategic sourcing providers, such as eBreviate and Ozro (formerly TradeAccess), allow buyers and sellers to negotiate non-price parameters, like incumbency, quality, delivery time and customer service, to arrive at a more complete picture of the cost of a product or service.

e-Marketplace software companies such as, Moai Technologies and MaterialNet have moved in a similar direction by offering applications that allow buyers to post requests for quotes (RFQs) that include parameters beyond price, such as product availability and lead-time, post-sales support and warranty, and certification standards. Buyers specify how important each parameter is to them using weighted scoring, and the software lets them compare how well responding suppliers meet the overall bidding criteria defined in the request for quote (RFQ) and the relative value of, say, going with a supplier offering a better warranty or shorter lead times.

New York-based ExpertCommerce is attempting to take this type of support one step further through an online purchase-evaluation engine for e-marketplaces. The engine is based on software developed by the company Expert Choice to provide offline decision support for Xerox, IBM and Ford. ExpertCommerce's application, dubbed eValuation Engine, incorporates a decision-making theory called analytic hierarchy process (AHP), which simulates the way humans process information. When buyers come to an e-marketplace to purchase a particular good, they specify priorities for product features or other criteria. The engine searches the e-marketplace's catalog to identify those products that most closely match the buyers' priorities. Buyers subsequently can adjust the weighting they assign to their priorities and see how those changes affect the list of products identified as the best fit. The software also allows buyers to compare products side-by-side.

The Plot Thickens

Perhaps the most ambitious project to quantify total cost of purchase is underway in Santa Fe, N.M., home of Prowess Software. Prowess is a division of the BiosGroup, which itself is a five-year-old joint venture between Cap Gemini Ernst & Young and complexity theorist Dr. Stuart Kauffman. Complexity science, which has been around since the 1950s, explores properties of such complex systems as economies, evolution or even ant colonies, all in an effort to understand commonalities between those systems and to define how the actions of individual actors within those systems affect the whole. Bios has been applying this science to the understanding of the complex business systems that have grown up in the past 20 years as corporations have increasingly automated their internal process and their connections with supply chain partners. Supply chains are particularly ripe for the application of complexity theory, asserts William Macready at Prowess, because they are so volatile and subject to perturbations, whether it's in demand or logistics snafus.

In its simplest form, Prowess' flagship application, MarketProwess, priced starting at $200,000 plus implementation and customization fees, takes an approach similar to that of other buyer-supplier matching and online negotiation engines. A buyer coming to an e-marketplace using MarketProwess defines an ideal trade for a particular product but also specifies flexibilities  tradeoffs that the buyer would be willing to accept for a user-defined set of parameters, such as delivery time, quantity, quality or price. Suppliers responding to the buyer's RFQ enter their own capabilities, indicating their price points, quality metrics, lead times, and so on. A matching engine processes the responses, calculates the total cost of purchase for each supplier and displays that information, as well as a measure of the buyer's subjective preferences for each supplier based, for instance, on a supplier report card system. Buyers can therefore determine which suppliers most closely meet their requirements, see the cost of their tradeoffs and set their own tolerance for additional expense based on the degree of flexibility they require in their supply chains. B2eMarkets announced in January that it would use MarketProwess to incorporate this type of functionality into its Strategic eSourcing Management product, a Web-based application that allows procurement professionals to access public and private e-marketplaces from their desktop computers.

Macready says the next step for Prowess is to incorporate its software into the workflow of a corporation's private online marketplace. In that setting, MarketProwess could draw information from enterprise resource planning (ERP), materials resource planning (MRP) and other internal systems to help define the flexibilities associated with each component, obviating the need for individual purchasers to set those parameters by hand each time they send out a RFQ. There is all this data out there around purchasing that is becoming accessible, Macready says. All those data sources actually do tell you what your preferences and flexibilities really are and can help guide the poor humans awash in all this sea of data.

Almost There

Are total-cost-of-purchase tools set to fully automate the supply chain? Not yet, according to Joseph Butt, a senior analyst with technology consultancy Forrester Research. It's really the machine-to-machine negotiation piece that we're looking for in true multi-attribute trading, and that just hasn't occurred, he says. The obstacles include the structure of supply chains themselves, which frequently revolve around an alpha dog-like channel master that can set the terms under which it trades with its partners.

Butt further asserts that the current models used to match buyers and suppliers are incapable of handling more than a handful of flexibilities for a single component, let alone dozens of parameters for thousands of components that go into a single, final product. The firepower isn't there yet, he explains, adding, I don't think that companies are going to spend a ton of money trying to straighten that out when they can't even get more simple models in the exchange world to actually work effectively.

Still, Butt says, People are moving toward it. The idea has merit, and we're going to look for a much higher level of coordination and integration. My guess is that ... in the three- to five-year range we're going to see some of this stuff coming to fruition. This will mean a better assessment of true and better pricing  a dream come true for the modern-day purchaser.